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Record W1546306710 · doi:10.18438/b8cw38

Larger, Higher-level Academic Institutions in the US Do Not Necessarily Have Better-resourced Library Web Teams.

2008· article· en· W1546306710 on OpenAlexvenueno aff
Suzanne Lewis

Bibliographic record

VenueEvidence Based Library and Information Practice · 2008
Typearticle
Languageen
FieldComputer Science
TopicWeb and Library Services
Canadian institutionsnot available
Fundersnot available
KeywordsStaffingWorld Wide WebSample (material)InstitutionLibrary scienceWeb pageHome pageMedical educationComputer scienceThe InternetPsychologySociologyMedicineSocial science

Abstract

fetched live from OpenAlex

A Review of:
 Connell, Ruth Sara. "Survey of Web Developers in Academic Libraries." The Journal of Academic Librarianship 34.2 (2008): 121-29.
 
 Objective – To discover how library Web teams’ staffing, backgrounds, tools, and professional development differ among various types of academic libraries.
 
 Design – Survey.
 
 Setting – Academic libraries in the United States.
 
 Subjects – Academic library Web team members.
 
 Methods – A systematic sample of every twelfth institution on The Carnegie Classification of Institutions of Higher Education list was used to establish a sample group. A Web search was carried out to identify each institution’s library Web site and contact information for the Web site designer or most appropriate alternative person. Institutions were excluded from the sample if they had no Web site at all, had no library Web site, had a Web site that did not mention a library, or had a Spanish-language Web site.
 
 In September 2006 an e-mail was sent to the contact for each institution in the sample group asking them to participate in an online survey. A follow up e-mail was sent two weeks later and the survey closed after one month. The survey respondents were asked to identify their institutions so that analysis of the results in relation to the size and type of institution could be carried out. The researchers used a simplified version of the Carnegie classification to sort the responding institutions into five main groups.
 
 Main Results – The systematic sample consisted of 288 institutions (sample size 6.5%).
 The profile of the responding institutions was as follows: associate’s colleges (35.5%), baccalaureate colleges (18.2%), master’s colleges and universities (20.9%), doctorate-granting universities (9%) and special focus institutions (15.5%). A total of 110 institutions completed the survey, yielding a response rate of 38.19%, although not all respondents answered all the survey questions. The final sample of 110 was 2.5% of the total 4384 institutions on the Carnegie list.
 
 Seventy-one per cent of institutions with multiple libraries shared Web teams, with two-year colleges more likely (91.7%) to share a Web team than four-year or above institutions (60.9%). The majority of responding institutions (94.4%) used in-house library Web site design, with only 5.6% of respondents outsourcing this task. Nearly half (49%) of respondents indicated that library Web design was done by one person and even the larger libraries did not necessarily have larger Web teams. 
 
 Very few Web team members (4.9%) had Web design as their primary role; the majority (83.5%) indicated that it was just one component of their job. Web team members from master’s- and doctorate-granting institutions were more likely to have taught themselves Web design, while those from associate, baccalaureate and special focus colleges were more likely to have taken Web design courses. For all respondents, the most commonly listed quality for selection to the Web team was an interest in Web design and the most valued skill for library Web designers was the ability to organise information effectively. Knowledge of Web authoring software and basic HTML coding were the most commonly listed knowledge requirements for Web team members. A significant number of respondents indicated that they or other Web team members did not have access to Web authoring (36.9%) and image editing (52%) software. 
 
 Generally (except for two very large institutions), the larger institutions were more likely to use database-driven systems for their library Web sites and the smaller institutions were more likely to use content management systems. Associate’s and special focus colleges were less likely than other types of institutions to use either database driven or content management systems. Associate’s institutions were more likely to achieve ADA (Americans with Disabilities Act) Web accessibility compliance. Only 48.6% of respondents utilised usability testing during Web site design.
 
 Conclusion – The author expected that institutions providing higher levels of education would have better-resourced Web design and training, but the results of the survey did not support this expectation. One reason why associate’s colleges performed better than other institutions in some areas of Web design may be that these colleges tend to offer more Web design and computer technology courses than baccalaureate, master’s and doctorate-granting institutions.
 
 Web site design and testing attracted fewer resources than might be expected in academic libraries. Across all types of institutions, Web design tended to be the responsibility of a small team or one person, with most Web designers having other responsibilities apart from the library’s Web site. Just over half of the institutions surveyed did not implement usability testing of their library Web sites.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.875
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.446
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.263
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2008
Admission routes1
Has abstractyes

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